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Álvaro Tejeda-Lorente
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- affiliation: University of Granada, Department of Computer Science and Artificial Intelligence
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2020 – today
- 2023
- [j13]Julio Herce-Zelaya
, Carlos Porcel
Introducing CSP Dataset: A Dataset Optimized for the Study of the Cold Start Problem in Recommender Systems. Inf. 14(1): 19 (2023) - 2020
- [j12]Carlos Porcel, Julio Herce-Zelaya
Trust Based Fuzzy Linguistic Recommender Systems as Reinforcement for Personalized Education in the Field of Oral Surgery and Implantology. Int. J. Comput. Commun. Control 15(3) (2020) - [j11]Julio Herce-Zelaya
New technique to alleviate the cold start problem in recommender systems using information from social media and random decision forests. Inf. Sci. 536: 156-170 (2020) - [j10]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
A context-aware embeddings supported method to extract a fuzzy sentiment polarity dictionary. Knowl. Based Syst. 190: 105236 (2020)
2010 – 2019
- 2019
- [c18]Julio Herce-Zelaya
Web platform for learning distributed databases' queries processing. ITQM 2019: 827-834 - [c17]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
An automatic skills standardization method based on subject expert knowledge extraction and semantic matching. ITQM 2019: 857-864 - [c16]Álvaro Tejeda-Lorente
A risk-aware fuzzy linguistic knowledge-based recommender system for hedge funds. ITQM 2019: 916-923 - 2018
- [j9]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
Leveraging Localized Social Media Insights for Industry Early Warning Systems. Int. J. Inf. Technol. Decis. Mak. 17(1): 357-385 (2018) - [j8]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
Quantifying the emotional impact of events on locations with social media. Knowl. Based Syst. 146: 44-57 (2018) - [c15]Julio Herce-Zelaya
Using Information Extracted from Microblogs in Order to Palliate the Cold Start Problem in Recommender Systems. SoMeT 2018: 347-360 - [c14]Álvaro Tejeda-Lorente
Adapting Recommender Systems to the New Data Privacy Regulations. SoMeT 2018: 373-385 - [c13]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
An Embeddings Based Fuzzy Linguistics Supported Model to Measure the Contextual Bias in Sentiment Polarity. SoMeT 2018: 735-748 - 2017
- [j7]Carlos Porcel, Alberto Ching-López, Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
Fuzzy Linguistic Recommender Systems for the Selective Diffusion of Information in Digital Libraries. J. Inf. Process. Syst. 13(4): 653-667 (2017) - [c12]Carlos Porcel, Alberto Ching-López, Álvaro Tejeda-Lorente
Analysis of Different Proposals to Improve the Dissemination of Information in University Digital Libraries. EUSFLAT/IWIFSGN (3) 2017: 195-206 - [c11]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
A Fuzzy Linguistics Supported Model to Measure the Contextual Bias in Sentiment Polarity. EUSFLAT/IWIFSGN (1) 2017: 199-210 - [c10]Álvaro Tejeda-Lorente
Using Bibliometrics and Fuzzy Linguistic Modeling to Deal with Cold Start in Recommender Systems for Digital Libraries. EUSFLAT/IWIFSGN (3) 2017: 393-404 - [c9]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
A Holistic Domain Knowledge Discovery and Recommendation System for Collaborative Wikis. SoMeT 2017: 99-114 - 2015
- [j6]Álvaro Tejeda-Lorente
REFORE: A recommender system for researchers based on bibliometrics. Appl. Soft Comput. 30: 778-791 (2015) - [j5]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
A new model to quantify the impact of a topic in a location over time with Social Media. Expert Syst. Appl. 42(7): 3381-3395 (2015) - [j4]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
CARESOME: A system to enrich marketing customers acquisition and retention campaigns using social media information. Knowl. Based Syst. 80: 163-179 (2015) - [c8]Álvaro Tejeda-Lorente, Carlos Porcel, Juan Bernabé-Moreno, Enrique Herrera-Viedma:
Recommending scientific papers through a method based on bibliometric measures. IFSA-EUSFLAT 2015 - [c7]Carlos Porcel, Carmen Martínez-Cruz
Integrating Ontologies and Fuzzy Logic to Represent User-Trustworthiness in Recommender Systems. ITQM 2015: 603-612 - [c6]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
Emotional Profiling of Locations Based on Social Media. ITQM 2015: 960-969 - [c5]Álvaro Tejeda-Lorente
A Dynamic Recommender System as Reinforcement for Personalized Education by a Fuzzly Linguistic Web System. ITQM 2015: 1143-1150 - 2014
- [j3]Álvaro Tejeda-Lorente
A quality based recommender system to disseminate information in a university digital library. Inf. Sci. 261: 52-69 (2014) - [j2]Bernabé Esteban, Álvaro Tejeda-Lorente
TPLUFIB-WEB: A fuzzy linguistic Web system to help in the treatment of low back pain problems. Knowl. Based Syst. 67: 429-438 (2014) - [c4]Álvaro Tejeda-Lorente
Integrating Quality Criteria in a Fuzzy Linguistic Recommender System for Digital Libraries. ITQM 2014: 1036-1043 - [c3]Juan Bernabé-Moreno, Álvaro Tejeda-Lorente
Leveraging Localized Social Media Insights for Early Warning Systems. ITQM 2014: 1051-1060 - [c2]Bernabé Esteban, Álvaro Tejeda-Lorente
Aiding in the Treatment of Low Back Pain by a Fuzzy Linguistic Web System. RSCTC 2014: 250-261 - 2012
- [j1]Carlos Porcel, Álvaro Tejeda-Lorente
A hybrid recommender system for the selective dissemination of research resources in a Technology Transfer Office. Inf. Sci. 184(1): 1-19 (2012) - 2011
- [c1]Álvaro Tejeda-Lorente
Using memory to reduce the information overload in a university digital library. ISDA 2011: 444-449
Coauthor Index
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